The use of spread spectrum technology for radionavigation or communications is well known in the electrical engineering arts. Spread spectrum communication is advantageous in communication applications requiring high reliability in a noisy environment. There are several types of spread spectrum systems, including direct sequence spread spectrum (“DSSS”) systems, frequency hopping systems, time hopping systems, pulse frequency modulated (or chirp) systems, and various hybrids. Of these, DSSS systems and frequency hopping systems are perhaps the more widely implemented. One system that uses DSSS technology is the Global Positioning System (“GPS”). The GPS is a constellation of satellites orbiting the earth and transmitting DS-SS signals. Receivers process signals from multiple satellites in order to determine their own position and location. GPS downlink signals are currently transmitted in two frequencies in L-band: L1, centered at 1575.42 MHz, and L2, centered at 1227.6 MHz.
When GPS was originally designed, it comprised two different downlink signals for radionavigation, corresponding to two different services. The precise positioning service (PPS), was intended for authorized (primarily US and Allied military) users, and employs the precision/encrypted (P(Y)) code signal. The standard positioning service (SPS) is available for use by any user worldwide, and employs the coarse acquisition (C/A) code signal. While the C/A code signal is currently transmitted only on L1, the P(Y) code signal is transmitted on both L1 and L2.
M-Code Signal for GPS and BOC Modulations
As part of GPS Modernization, the U.S. Government is adding new signals in addition to the existing GPS signals. The C/A-code signal (or a signal with identical modulation but different spreading code and data modulation) will be transmitted on L2. In addition, a new signal for military use (the M-code signal) will be transmitted on both L1 and L2. The M-code signal is designed to provide additional capabilities and performance, especially enhanced jamming resistance, while remaining compatible with reception of current GPS signals.
The M-code signal uses a novel modulation, denoted binary offset carrier (“BOC”), which contributes both to performance and to spectral compatibility with existing signals. BOC modulations are described by their subcarrier rate and their spreading code rate; the M-code signal uses a subcarrier rate of 10.23 MHz and a spreading code rate of 5.115 MHz. Other developments of advanced radionavigation systems, including the European Galileo development, are also considering the use of BOC modulations, possibly with different subcarrier rates and spreading code rates. One critical characteristic of BOC modulations is that they typically offer much narrower correlation function peaks, providing better ranging accuracy in noise and multipath. For a more detailed description of BOC signals and their properties, see John W. Betz, The Offset Carrier Modulation for GPS Modernization, Proceedings of ION 1999 National Technical Meeting, Institute of Navigation; Brian C. Barker et al., Overview of the GPS M Code Signal, Proceedings of ION 2000 National Technical Meeting, and John W. Betz, Binary Offset Carrier Modulations for Radionavigation, Navigation: The Proceedings of the Institute of Navigation, Fall/Winter 2001–2002. The contents of these articles are hereby incorporated by reference.
Direct Acquisition of Signals with BOC Modulations
GPS satellites that transmit the M code signal will be launched as early as in 2003. New receivers are being developed for reception and processing of the M-code signal. An essential aspect of GPS signal receiver processing is signal acquisition, where the receiver aligns its internal timing and frequency to the precise values of the received signal. Before acquisition begins, the receiver's internal timing and frequency references are in error by certain amounts. The sizes of these errors depend upon a number of factors, including operational conditions, receiver design, and signal design.
Direct acquisition, where the receiver performs acquisition without use of transmitted acquisition aids, involves cross-correlating a locally generated reference signal against time and frequency-shifted versions of a received signal. In DSSS processing, the reference signal is a replica of the pseudo-noise (PN) sequence code used to spread the spectrum of the received signal at a transmitter. The ability of a DSSS system to suppress radio-interference is directly proportional to the ratio of the PN code symbol, or “chip”, rate to the data rate. The cross-correlation over both time lag and frequency offset is termed a complex ambiguity function. The coordinates of the location where the magnitude of the cross-ambiguity function achieves a maximum (or “peak”) reveal the time lag and frequency offset that align the reference signal with the received signal.
Direct acquisition is the baseline approach for acquisition of the M code signal. FIG. 1 is helpful in understanding direct acquisition processing. Direct acquisition involves a search over a set of time and frequency values that represent the receiver's uncertainty region 102, which is typically quantized into discrete time and frequency cells 104. The receiver performs multiply-accumulate processing to compute a test statistic (or “metric”) for each time-frequency cell 104. Appropriate time lags (or “code offsets”) and frequency offsets are determined by testing the metrics to determine if they exceed a predetermined threshold indicating synchronization. All cells 106 whose metrics exceed the threshold typically undergo a verification process before the acquisition processing declares that the signal has been acquired.
Major contributors to time uncertainty window 108, which can vary from a few spreading code periods to millions of spreading code chip periods, include the absolute and relative inaccuracy of system clocks, an unknown distance between the transmitter and receiver, and the code period. Typically, the time-domain extent of a cell 110 is one-half a chip period (i.e., the distance between the cross-ambiguity function's peak and its first zero).
Unknown Doppler shifts and the drift of a receiver's oscillator are major sources of frequency uncertainty 112 and can range from tens of hertz for stationary transmitters and receivers to kilohertz for receivers and transmitters installed in high-speed platforms. The frequency-domain extent of a cell 114 is typically half the reciprocal of the coherent integration time being used in direct acquisition processing.
The search over the time and frequency uncertainty region 102 can be performed as a serial search or a parallel search. One difference between serial search methods and parallel acquisition methods is the number of cells 104 searched at one time. Serial search methods compute and analyze one time-frequency cell 104 at a time. Parallel methods, on the other hand, are primarily distinguished by the selected implementation method of short-time correlation processing and by the number of cross-correlations being calculated simultaneously. Parallel methods compute quantized correlation “tiles” 116 containing multiple time-frequency cells 104. For example, tiles could be dimensioned to be 5 milliseconds by 800 Hz in size.
Parallel methods are frequently implemented in hardware by using code-matched filters (CMFs), which calculate new correlation samples at a rate proportional to the rate at which the received signal is sampled. CMFs use finite-impulse response-like structures to correlate input signals fed into them with the locally-generated reference signal. Within CMFs, spreading code values are treated as filter taps and are stored in semi-permanent registers. CMFs are versatile because they can be implemented using time-domain methods, frequency-domain methods, or a combination of the two.
Existing designs for direct acquisition process the signal over its entire bandwidth, using digital processing with a sampling rate established to ensure that at least two samples fall on the peak of the cross-ambiguity (or “correlation”) function. Since the M-code signal's correlation function has a narrow peak, this approach would require high sampling rates. And because the rate of arithmetic operations needed for direct acquisition processing is roughly proportional to the square of the sampling rate, existing approaches lead to computationally complex methods for direct acquisition of BOC modulations. In fact, skilled practitioners in spread spectrum signal acquisition have indicated that unaided direct acquisition using CMF architectures of the M code signal is extremely complex, and implementations would not be practical for many years.